I had a lengthy discussion with Eric today and clarified some things in
my mind about the future directions of scipy. The following is
basically what we have decided. We are still interested in input so
don't think the issues are closed, but I'm just giving people an idea
of my (and Eric's as far as I understand it) thinking on scipy.
1) There will be a scipy_core package which will be essentially what
Numeric has always been (plus a few easy to install extras already in
current scipy_core). It will likely contain the functionality of (the
names and placements will be similar to current scipy_core).
Numeric3 (actually called ndarray or narray or numstar or numerix or
something....)
fft (based on c-only code -- no fortran dependency)
linalg (a lite version -- no fortran or ATLAS dependency)
stats (a lite version --- no fortran dependency)
special (only c-code --- no fortran dependency)
weave
f2py? (still need to ask Pearu about this)
scipy_distutils and testing
matrix and polynomial classes
...others...?
We will push to make this an easy-to-install effective replacement for
Numeric and hopefully for numarray users as well. Therefore community
input and assistance will be particularly important.
2) The rest of scipy will be a package (or a series of packages) of
algorithms. We will not try to do plotting as part of scipy. The
current plotting in scipy will be supported for a time, but users will
be weaned off to other packages: matplotlib, pygist (for xplt -- and I
will work to get any improvements for xplt into pygist itself),
gnuplot, etc.
3) Having everything under a scipy namespace is not necessary, nor worth
worrying about at this point.
My scipy-related focus over the next 5-6 months will be to get
scipy_core to the point that most can agree it effectively replaces the
basic tools of Numeric and numarray.
-Travis